Publications

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Poster
Baboulin, M., V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, and S. Tomov, Towards a High-Performance Tensor Algebra Package for Accelerators , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC15), September 2015.  (1.76 MB)
Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.  (3.01 MB)
Presentation
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, et al., Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched , Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.  (9.29 MB)
Nath, R., S. Tomov, E. Agullo, and J. Dongarra, Autotuning Dense Linear Algebra Libraries on GPUs , Basel, Switzerland, Sixth International Workshop on Parallel Matrix Algorithms and Applications (PMAA 2010), June 2010.  (579.44 KB)
Yamazaki, I., M. Hoemmen, P. Luszczek, and J. Dongarra, Comparing performance of s-step and pipelined GMRES on distributed-memory multicore CPUs , Pittsburgh, Pennsylvania, SIAM Annual Meeting, July 2017.  (748 KB)
Danalis, A., H. Jagode, and J. Dongarra, Does your tool support PAPI SDEs yet? , Tahoe City, CA, 13th Scalable Tools Workshop, July 2019.  (3.09 MB)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Flexible Batched Sparse Matrix Vector Product on GPUs , Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.  (16.8 MB)
Tomov, S., and J. Dongarra, The Future of Computing: Software Libraries , Savannah, GA, DOD CREATE Developers' Review, Keynote Presentation, February 2012.  (6.76 MB)
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
Tomov, S., J. Dongarra, A. Haidar, I. Yamazaki, T. Dong, T. Schulthess, and R. Solcà, MAGMA: A Breakthrough in Solvers for Eigenvalue Problems , San Jose, CA, GPU Technology Conference (GTC12), Presentation, May 2012.  (9.23 MB)
Dongarra, J., T. Dong, M. Gates, A. Haidar, S. Tomov, and I. Yamazaki, MAGMA: A New Generation of Linear Algebra Library for GPU and Multicore Architectures , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), Presentation, November 2012.  (4.69 MB)
Tomov, S., and J. Dongarra, MAGMA - LAPACK for HPC on Heterogeneous Architectures , Oak Ridge, TN, Titan Summit at Oak Ridge National Laboratory, Presentation, August 2011.  (20.43 MB)
Dongarra, J., M. Gates, Y. Jia, K. Kabir, P. Luszczek, and S. Tomov, MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), November 2012.  (6.4 MB)
Anzt, H., J. Dongarra, M. Gates, A. Haidar, K. Kabir, P. Luszczek, S. Tomov, and I. Yamazaki, MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi , Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, June 2015.  (2.03 MB)
Ng, L., S. Chen, A. Gessinger, D. Nichols, S. Cheng, A. Meenasorna, K. Wong, S. Tomov, A. Haidar, E. D'Azevedo, et al., MagmaDNN 0.2 High-Performance Data Analytics for Manycore GPUs and CPUs : University of Tennessee, January 2019. DOI: 10.13140/RG.2.2.14906.64961  (7.84 MB)
Ng, L., K. Wong, A. Haidar, S. Tomov, and J. Dongarra, MagmaDNN – High-Performance Data Analytics for Manycore GPUs and CPUs , Knoxville, TN, 2017 Summer Research Experiences for Undergraduate (REU), Presentation, December 2017.  (5.06 MB)
Danalis, A., H. Jagode, and J. Dongarra, PAPI: Counting outside the Box , Barcelona, Spain, 8th JLESC Meeting, April 2018.
Jagode, H., A. Danalis, and J. Dongarra, PAPI's New Software-Defined Events for In-Depth Performance Analysis , Lyon, France, CCDSC 2018: Workshop on Clusters, Clouds, and Data for Scientific Computing, September 2018.
Danalis, A., H. Jagode, and J. Dongarra, PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.  (3.14 MB)
Haidar, A., H. Jagode, A. YarKhan, P. Vaccaro, S. Tomov, and J. Dongarra, Power-Aware HPC on Intel Xeon Phi KNL Processors , Frankfurt, Germany, ISC High Performance (ISC17), Intel Booth Presentation, June 2017.  (5.87 MB)
Danalis, A., H. Jagode, and J. Dongarra, Software-Defined Events through PAPI for In-Depth Analysis of Application Performance , Basel, Switzerland, 5th Platform for Advanced Scientific Computing Conference (PASC18), July 2018.
Danalis, A., H. Jagode, D. Barry, and J. Dongarra, Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.  (2.33 MB)
Jagode, H., A. Danalis, and J. Dongarra, What it Takes to keep PAPI Instrumental for the HPC Community , Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.  (3.29 MB)
Danalis, A., H. Jagode, and J. Dongarra, Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.  (2.5 MB)
Tech Report
Dongarra, J., J. Demmel, J. Langou, and J. Langou, 2016 Dense Linear Algebra Software Packages Survey,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-744 / LAWN 290: University of Tennessee, September 2016.  (366.43 KB)
Anzt, H., S. Tomov, and J. Dongarra, Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-731: University of Tennessee, October 2014.  (1.83 MB)
Tomov, S., and J. Dongarra, Accelerating the Reduction to Upper Hessenberg Form through Hybrid GPU-Based Computing,” University of Tennessee Computer Science Technical Report, UT-CS-09-642 (also LAPACK Working Note 219), May 2009.  (2.37 MB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, Achieving Numerical Accuracy and High Performance using Recursive Tile LU Factorization,” University of Tennessee Computer Science Technical Report (also as a LAWN), no. ICL-UT-11-08, September 2011.  (618.53 KB)
Chen, Z., and J. Dongarra, Algorithm-Based Checkpoint-Free Fault Tolerance for Parallel Matrix Computations on Volatile Resources,” University of Tennessee Computer Science Department Technical Report, vol. –05-561, November 2005.  (266.54 KB)
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, Algorithm-based Fault Tolerance for Dense Matrix Factorizations,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-676, Knoxville, TN, August 2011.  (865.79 KB)
Bosilca, G., R. Delmas, J. Dongarra, and J. Langou, Algorithmic Based Fault Tolerance Applied to High Performance Computing,” University of Tennessee Computer Science Technical Report, UT-CS-08-620 (also LAPACK Working Note 205), January 2008.  (313.55 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.  (358.98 KB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-09: Innovative Computing Laboratory, University of Tennessee, September 2018.  (3.74 MB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-11-666, (also Lawn 243), 00 2011.  (1.65 MB)
Luszczek, P., and J. Dongarra, Analysis of Various Scalar, Vector, and Parallel Implementations of RandomAccess,” Innovative Computing Laboratory (ICL) Technical Report, no. ICL-UT-10-03, June 2010.  (226.9 KB)
Song, F., S. Moore, and J. Dongarra, Analytical Modeling for Affinity-Based Thread Scheduling on Multicore Platforms,” University of Tennessee Computer Science Technical Report, UT-CS-08-626, January 2008.  (650.75 KB)
Bosilca, G., A. Bouteiller, T. Herault, Y. Robert, and J. Dongarra, Assessing the impact of ABFT and Checkpoint composite strategies,” University of Tennessee Computer Science Technical Report, no. ICL-UT-13-03, 2013.  (968.47 KB)
Emad, N., S. A. S. Fazeli, and J. Dongarra, An Asynchronous Algorithm on NetSolve Global Computing System,” PRiSM - Laboratoire de recherche en informatique, Université de Versailles St-Quentin Technical Report, March 2004.  (377.33 KB)
Seymour, K., H. You, and J. Dongarra, ATLAS on the BlueGene/L – Preliminary Results,” ICL Technical Report, no. ICL-UT-06-10, January 2006.  (46.19 KB)
Whaley, C., A. Petitet, and J. Dongarra, Automated Empirical Optimizations of Software and the ATLAS Project (LAPACK Working Note 147),” University of Tennessee Computer Science Department Technical Report,, no. UT-CS-00-448, September 2000.  (373.69 KB)
You, H., K. Seymour, J. Dongarra, and S. Moore, Automated Empirical Tuning of a Multiresolution Analysis Kernel,” ICL Technical Report, no. ICL-UT-07-01, pp. 10, January 2007.  (120.7 KB)
Kurzak, J., S. Tomov, and J. Dongarra, Autotuning GEMMs for Fermi,” University of Tennessee Computer Science Technical Report, UT-CS-11-671, (also Lawn 245), April 2011.  (397.45 KB)
Anzt, H., E. Chow, and J. Dongarra, On block-asynchronous execution on GPUs,” LAPACK Working Note, no. 291, November 2016.  (1.05 MB)
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, A Block-Asynchronous Relaxation Method for Graphics Processing Units,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-687 / LAWN 258, November 2011.  (1.08 MB)
Abdelfattah, A., K. Arturov, C. Cecka, J. Dongarra, C. Freitag, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, et al., C++ API for Batch BLAS,” SLATE Working Notes, no. 4, ICL-UT-17-12: University of Tennessee, December 2017.  (1.89 MB)
Gates, M., P. Luszczek, A. Abdelfattah, J. Kurzak, J. Dongarra, K. Arturov, C. Cecka, and C. Freitag, C++ API for BLAS and LAPACK,” SLATE Working Notes, no. 2, ICL-UT-17-03: Innovative Computing Laboratory, University of Tennessee, June 2017.  (1.12 MB)
Fayad, D., J. Kurzak, P. Luszczek, P. Wu, and J. Dongarra, The Case for Directive Programming for Accelerator Autotuner Optimization,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-07: University of Tennessee, October 2017.  (341.52 KB)
Buttari, A., J. Langou, J. Kurzak, and J. Dongarra, A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures,” University of Tennessee Computer Science Technical Report, no. UT-CS-07-600 (also LAPACK Working Note 191), January 2007.  (274.74 KB)
Cao, C., J. Dongarra, P. Du, M. Gates, P. Luszczek, and S. Tomov, clMAGMA: High Performance Dense Linear Algebra with OpenCL,” University of Tennessee Technical Report (Lawn 275), no. UT-CS-13-706: University of Tennessee, March 2013.  (526.6 KB)

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